Application of fuzzy time series and fuzzy ontology integration in diagnostics of technical systems

The method of constructing fuzzy ontologies was investigated in the framework of this work. An ontological model for assessing the state of helicopter units has been developed. The article provides a formal description of fuzzy ontologies and features of the representation of elements of fuzzy axioms in FuzzyOWL notation. According to the proposed approach, the summarizing of the state of a complex technical system is carried out by means of a logical inference based on a fuzzy ontology. Objects, properties and axioms of fuzzy ontology determine the parameters of the membership functions and linguistic variables of the objects of analysis in the form of time series. A software product was developed to implement the proposed approach. As part of this work, experiments were conducted to search for anomalous situations and search for possible faulty helicopter units using the developed approach to the integration of fuzzy time series and fuzzy ontology. For the first time, the results of the logical inference of knowledge based on the integration of fuzzy time series and fuzzy ontologies in the tasks of analyzing the diagnosis of complex technical systems were obtained. The proposed approach of hybridization of fuzzy time series and fuzzy ontologies made it possible to reliably recognize anomalous situations with a certain degree of truth, and to find possible faulty aggregates corresponding to each anomalous situation.